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©2024 International Monetary Fund
SDN/2024/001
IMF Staff Discussion Notes
Research Department
Gen-AI: Artificial Intelligence and the Future of Work
Prepared by Mauro Cazzaniga, Florence Jaumotte, Longji Li, Giovanni Melina, Augustus J. Panton, Carlo Pizzinelli, Emma Rockall, and Marina M. Tavares*
Authorized for distribution by Pierre-Olivier Gourinchas
January 2024
IMF Staff Discussion Notes (SDNs) showcase policy-related analysis and research being developed by IMF staff members and are published to elicit comments and to encourage debate. The views expressed in Staff Discussion Notes are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
ABSTRACT: Artificial intelligence (AI) has the potential to reshape the global economy, especially in the realm of labor markets. Advanced economies will experience the benefits and pitfalls of AI sooner than emerging market and developing economies, largely because their employment structure is focused on cognitive-intensive roles. There are some consistent patterns concerning AI exposure: women and college-educated individuals are more exposed but also better poised to reap AI benefits, and older workers are potentially less able to adapt to the new technology. Labor income inequality may increase if the complementarity between AI and high-income workers is strong, and capital returns will increase wealth inequality. However, if productivity gains are sufficiently large, income levels could surge for most workers. In this evolving landscape, advanced economies and more developed emerging market economies need to focus on upgrading regulatory frameworks and supporting labor reallocation while safeguarding those adversely affected. Emerging market and developing economies should prioritize the development of digital infrastructure and digital skills.
RECOMMENDED CITATION: Cazzaniga and others. 2024. “Gen-AI: Artificial Intelligence and the Future of Work.” IMF Staff Discussion Note SDN2024/001, International Monetary Fund, Washington, DC.
| ISBN: | 979–8-40026–254-8 |
| JEL Classification Numbers: | E24, J24, J31, O33, O38 |
| Keywords: | Artificial Intelligence, Labor Market, Job Displacement, Income Inequality, Advanced Economies, Emerging Market Economies, Low-Income Developing Countries |
| Author’s E-Mail Address: | mauro98cazzaniga@gmail.com, FJaumotte@imf.org, LLi4@imf.org, GMelina@imf.org, APanton@imf.org, CPizzinelli@imf.org, ERockall@stanford.edu, MMendestavares@imf.org |
| ISBN: | 979–8-40026–254-8 |
| JEL Classification Numbers: | E24, J24, J31, O33, O38 |
| Keywords: | Artificial Intelligence, Labor Market, Job Displacement, Income Inequality, Advanced Economies, Emerging Market Economies, Low-Income Developing Countries |
| Author’s E-Mail Address: | mauro98cazzaniga@gmail.com, FJaumotte@imf.org, LLi4@imf.org, GMelina@imf.org, APanton@imf.org, CPizzinelli@imf.org, ERockall@stanford.edu, MMendestavares@imf.org |
Contents
Executive Summary
I. Introduction
II. AI Exposure and Complementarity
III. Worker Reallocation in the AI-Induced Transformation
IV. AI, Productivity, and Inequality
V. AI Preparedness
VI. Conclusions and Policy Considerations
Annex I. Data
Annex 2. Additional Information on AI Occupational Exposure and Potential Complementarity
Annex 3. Methodology for the Worker Transition Analysis
Annex 4. Model Details
Annex 5. AI Preparedness Index
References
Boxes
1. AI Occupational Exposure and Potential Complementarity1
2. Artificial-Intelligence-led Innovation and the Potential for Greater Inclusion1
Figures
1. Employment Shares by AI Exposure and Complementarity: Country Groups and Select
2. Employment Share by Exposure and Complementarity (Selected Countries)
3. Share of Employment in High-Exposure Occupations by Demographic Groups
4. Share of Employment in High-Exposure Occupations by Income Deciles
5. Occupational Transitions for College-Educated High-Exposure Workers for BRA and GBR
6. Life Cycle Profiles of Employment Shares by Education Level for Brazil and the United
7. 1-Year Re-Employment Probability of Separated Workers
8. Estimated Wage Premia from Occupation Changes
9. Exposure to AI and to Automation and Income in the UK
10. Change in Total Income by Income Percentile
11. Impact on Aggregates (Percentage
12. AI Preparedness Index and
13. ICT Employment Share and Individual Components of the AI Preparedness Index
EDITOR’S NOTE (3/1/24)
A correction has been made to Annex Table 5.1, which displays the AI Preparedness Indicators. Specifically, the indicator under dimension IV, Regulation and Ethics, has been modified from “Overall governance” to “Government effectiveness”.
The authors thank Pierre-Olivier Gourinchas and Antonio Spilimbergo for feedback and guidance and many IMF colleagues for useful comments. The views expressed herein are those of the authors and should not be attributed to the IMF, its Executive Board, or its management. Any remaining errors are the responsibility of the authors.